What’s happened in AI: May 7th-13th

Busy week in many different areas of the AI world. Highlights include Google hosting their annual I/O festival for developers, and the White House finallytaking concrete steps to foster AI collaboration between the private sector and government by hosting an AI summit.

Meanwhile, on the autonomous vehicle front, Drive.AI announced a ride-haling services pilot program in Texas that will launch in July. If this goes well, it could be a huge boost to the company and future programs of similar nature. I’m personally a huge fan of Drive.AI and they were one of two companies I pitched in my AI VC thesis. They’ve raised a $50mm Series B, partnered with Lyft, and named Andrew Ng to the board since my pitch in early June 2017. Look forward to seeing what the Drive.AI team will achieve in the future.

The company is allowed to test autonomous vehicles in the state as of May 10, according to the California Department of Motor Vehicles’ website

Didi has been expanding around the world mostly through investing in and partnering with competitors. The taxi firm acquired control of Brazilian taxi start-up 99 Taxi earlier this year, and has teamed up with other upstarts including Tallinn, Estonia-based Taxify and Dubai, United Arab Emirates-based Careem

Didi made its first direct expansion outside of China into Mexico last month. It is reportedly holding talks about a listing that could help it reach a valuation of between $70 billion and $80 billion.

Custom-designed vehicles could be owned or leased by individual customers, including those outside of large cities, and used in peer-to-peer car sharing applications, said Mike Abelson, GM’s vice president of global strategy. GM is “thinking about several models” to drive revenue from self-driving cars, according to Mr. Abelson, speaking at Citi’s Car of the Future conference in New York

Early leaders in deploying self-driving cars, such as GM and Alphabet Inc.’s Waymo, “will have the opportunity to take a lead in new business models that will drive their companies’ profitability,” said John Hoffecker, vice chairman of AlixPartners

Mr. Hoffecker said costs are “going down dramatically,” to the point where individuals should be able to buy self-driving cars by 2023-25.

The Google Lens is bringing together the sheer capabilities of Google Search with the latest development in the field of Computer Vision and Natural Language Processing. In the process, Google provides a strong idea as to why the approach taken by Google regarding the development of Artificial Intelligence will be of use to people right away, as compared to the other tech giants like Amazon and Facebook

Google Lens is the platform by Google for observing, interpreting and subsequently augmenting the reality. It is a part of the camera viewfinder of the applications from Google like Assistant and now it will be a part of the default camera application of the leading phones. The target of Lens is to provide customers an idea about their surrounding and all the constituent objects, which are part of that surrounding. This includes objects and the surrounding, humans, animals and all forms of text available on sign boards, hoardings, books or menu cards. These images are then cross-referred using the Knowledge Base of Google Search to provide insights like background from Wikipedia or e-commerce website links

Uber CEO Dara Khosrowshahi says that the company plans to put self-driving cars back on the road “within the next few months.” The transportation company suspended tests in March after one of its vehicles struck and killed a pedestrian in Arizona. The incident is believed to be the first human death from an autonomous car

Speaking at the Uber Elevate summit in Los Angeles yesterday, Khosrowshahi was quick to point out that Uber proactively ceased its autonomous driving tests after the death, failing to mention that the state of Arizona also ordered Uber to stop the program

“It’ll be within the next few months… I don’t know, and the time will be right when the time is right because we’re doing a top to bottom safety review, both internally and with independent safety folks coming in to take a look at our culture, our practices, etc,” Khosrowshahi said

Notch up another win for the robots: the latest program from Google’s artificial intelligence group, DeepMind, has trounced experts at a maze game after it learned to find its way around like a human

Scientists noticed that when they trained the AI to move through a landscape, it spontaneously developed electrical activity akin to that seen in the specialised brain cells that underpin human navigational skills. So-called ‘grid cells’ were only identified in animals in 2005 in work that earned researchers a Nobel prize

After discovering the AI-made grid cells, the DeepMind researchers made a beefed-up version of the program. It went on to beat experienced players at a game that involved racing through rooms to find a prize after being dropped into the virtual environment at a random location. Equipped with the artificial grid cells, the AI was faster and found shortcuts that would occasionally crop up when doors in the environment suddenly opened

Because we’re using more learned systems than traditional sort of hand-coded software, I think that raises a lot of challenges for us that we’re tackling,” John Giannandrea said. “So one is if you learn from data and that data has biased decisions in it already, then the machine learning models who learn can themselves perpetuate those biases. And so there’s a lot of work that we’re doing, and others in the machine learning community, to figure out how we can train machine learning models that don’t have forms of bias.”

Today, the implementation of AI in Google products goes through an internal review process, Dean said. Google is currently developing a set of guidelines for how to assess whether or not an AI model contains bias. “What you want is essentially, just like security review or privacy review for new features in products, you want an ML fairness review that’s part of integrating machine learning into our products,” John Giannandrea said

A team of Microsoft interns have thought up a new way to put A.I. technology to work – in a screenshot snipping tool. Microsoft today is launching their project, Snip Insights, a Windows desktop app that lets you retrieve intelligent insights – or even turn a scan of a textbook or report into an editable document – when you take a screenshot on your PC

Their new tool leverages Cloud AI services in order to do more with screenshots – like convert images to translated text, automatically detect and tag image content, and more.

For example, you could screenshot a photo of a great pair of shoes you saw on a friend’s Facebook page, and the tool could search the web to help you find where to buy them. (This part of its functionality is similar to what’s already offered today by Pinterest). The tool can also take a scanned image of a document, and turn a screenshot of that into editable text. And it can identify famous people, places or landmarks in the images you capture with a screenshot

Although it’s a relatively narrow use case for A.I., the Snip Insights tool is an interesting example of how A.I. technology can be integrated into everyday productivity tools – and the potential that lies ahead as A.I. becomes a part of even simple pieces of software

Sitel Group, one of the largest customer experience management companies in the world, announced that it has appointed Alexandre Lebrun, head of Engineering at Facebook Artificial Intelligence Research (FAIR), to its board of directors – a move that signals the company’s continued progression toward offering artificially intelligent digital solutions to its clients

Alexandre joins the Sitel Group board of directors at an exciting time as the company continues to invest in technology and services to revolutionize customer experience management. Specifically, Alexandre’s experience with artificial intelligence (AI), machine learning, chatbots, natural language processing (NLP) and more will be a key asset in driving the Sitel Group in its mission to leverage data to create conversational value and meaningful connections for customers and their consumers on Facebook Messenger

Alexandre Lebrun has more than 15 years of experience in the AI field with some of the most well-known companies in the NLP and conversational interface market, including Wit.ai, an AI platform that makes it easy for developers to create applications that users can talk to in natural language. He co-founded and led the company as CEO until its acquisition by Facebook in 2015. Prior to co-founding Wit.ai, Alexandre was the founder and CEO of VirtuOz, the pioneer and leader in virtual agents for customer service

Stock photo giant Shutterstock has launched a bunch of AI-infused search tools through a new online channel designed to showcase its latest R&D efforts. Shutterstock Showcase, formerly known as Shutterstock Labs, will now serve as the company’s public-facing portal for everything it’s working on related to artificial intelligence

The company has launched a new Chrome extension called Shutterstock Reveal that allows you to choose any image from the internet and find a similar royalty-free incarnation in Shutterstock’s library. This follows a similar reverse image search tool it launched two years back within the main Shutterstock app

Shutterstock also announced Copy Space, a computer vision-based tool that lets you search for images that have open “space” in a particular area of a photo where you can easily add text or graphics

Google Research has just published a research paper detailing a new algorithm that proposes a new way to answer queries. If in the future this algorithm is put into place it will further change the influence of traditional ranking factors for determining what gets ranked. In the short term, this research provides an insight into what Google means when they say that an algorithm update was made to improve relevance

What is new is that this is a machine learning algorithm that uses Reinforcement Learning approach. Furthermore, the algorithm has no knowledge of how the ranking system works. It is asking questions from what a black box algorithm then learning. This new algorithm uses a learning system that reformulates the user query, asking the ranking engine many questions, then choosing the best answers from the multiple sets of answers

Live Nation and Ticketmaster suggested they’ll try to develop the ability for concert goers to attend using facial recognition last week, when announcing an investment in Blink Identity. Blink is a brand new company that claims to be able to identify people walking by in “half a second,” even if they aren’t looking straight at a camera

While that sounds convenient, it also means that concert venues would have to be outfitted with surveillance equipment. And on perhaps an even worse note, it means that Ticketmaster — a company everyone hates more with each new convenience fee tacked onto their bill — would need to develop a database of all its concertgoers’ faces, which a lot of people aren’t going to be comfortable with

In July, Drive.ai, a Mountain View, California-based startup, plans to launch a six-month pilot program in Frisco, a small city in the Dallas-Fort Worth metro area.

The Frisco pilot will use the Nissan NV200, the same boxy van that roams New York City streets as a yellow taxi. Drive.ai is starting small with just four vehicles that will operate during weekday daylight hours, serving an office park complex where about 10,000 people work. Much like hailing an Uber, riders will summon one of Drive.ai’s vehicles using an app they install on their phones. For now, rides are free

Drive.ai was founded inflate 2015 by a group of deep-learning experts at Stanford University. It develops technology that can be used to modify various vehicles into autonomous vehicles; the small fleet the company is testing in California includes three Lincoln MKZs, an Audi A4, and three Nissan NV200s. Drive.ai has raised about $77 million, most recently adding $15 million from investors including Grab, the largest ride-hailing firm in Southeast Asia, in September 2017. Andrew Ng, an artificial intelligence guru, sits on Drive.ai’s board

At Microsoft’s annual developer conference, the company announced a slew of new tools for its Microsoft 365 suite, which combines Windows 10, Office 365 and its Enterprise Mobility + Security package. Among the additions is Windows Machine Learning, a new platform that will help developers create machine learning models in the intelligent cloud and then put them into use

Microsoft already uses AI in its Office 365 suite, inside the Windows 10 Photos app, with Windows Hello facial recognition as well as in services that aid cybersecurity professionals and help advertisers. And soon, with the next major Windows 10 update, developers will get access to Microsoft’s AI tools and be able to use them to build Windows 10 apps

With Windows Machine Learning, developers will be able to use pre-trained machine learning models, ensuring real-time analysis of data for lower costs. And the AI platform can be used across a number of devices including IoT edge devices, HoloLens, desktop PCs, workstations, servers and data centers

There are now 30,000 active bots per month that use Microsoft’s conversational AI tools. They handle 30 million messages per day for a thousand companies, including Macy’s, Asiana Airlines, Stack Overflow, KPMG, Telefonica, HP and UPS

Microsoft’s Bot Builder SDK has been updated. It lets you pick a bot design and then create your own bot from this model. Starting today, QnAMaker is now also available as a final release. It lets you turn a good old FAQ into a set of questions and answers for your bot

There’s also two new projects called Project Conversation Learner and Project Personality Chat. With the first project, you can feed conversations into the platform and let Microsoft use machine learning to learn new dialogue sequences. And the second project lets you create some small talk interactions to create the illusion that you’re talking with a real person

SAP is continuing to add smart features to its cloud enterprise resource planning (ERP) solution – S/4HANA Cloud – as it looks to help customers automate processes and react faster to information held in their core systems. It has also integrated S/4HANA with CoPilot, its digital assistant, allowing users to take action through a natural language interface, like Microsoft’s Cortana

The 1805 release of S/4HANA Cloud, which is out today, will include 12 new ‘scenarios’ to help customers optimise common processes. Nine of these are machine learning solutions and three are CoPilot ‘conversational UI scenarios’

For finance there is automatic account reconciliation powered by machine learning, with the system making recommendations, instead of relying on manual resolutions. Sales can now create orders from sales quotes using a conversational user experience. For project managers there is an AI-powered project cost forecasting feature which promises to reduce budget overruns

Specifically, the accounting provider’s personalised machine learning systems delivered more than 750 million invoice and bill code recommendations, and more than 250 million bank reconciliation recommendations since the features were first launched in March last year

Across the 800,000 invoices filed every day in Xero, the company said that small businesses have “collectively saved” in excess of 307 hours per day during the first 12 months

Tailor Brands, a company that uses artificial intelligence (AI) to create company brands, has raised $15.5 million in a series B round of funding led by Pitango Venture Capital Growth Fund and the U.K.’s Armat Group, with participation from Mangrove Capital Partners and Disruptive Technologies

Founded in 2014, Tailor Brands adopts an ethos similar to that of design marketplaces such as 99designs, insofar as it targets non-designers with a platform that does everything for them. However, Tailor Brands has one key difference: Its designs are carried out by robots. Or, to put it more accurately, algorithms

“When a user chooses a Tailor-designed logo, social post, or business card, the user validates Tailor’s alteration of an initial set of designs,” Tailor Brands CEO and cofounder Yali Saar told VentureBeat. “By doing so, they increase the AI’s level of accuracy for a certain variation. Once enough people validate a variation, Tailor is able to add it to its portfolio. This ‘training’ process enhances the [number] of structures, styles, color variations, and so on.” So it works much like other neural network systems, by leaning heavily on “supervised” learning via previously validated design data. As it can learn, it should continue to improve over time

Between Microsoft Build and Google I/O, there are probably more people saying “AI” this week than any previous week in history. But the AI those companies deploy tends to live off in a cloud somewhere — XNOR puts it on devices that may not even be capable of an internet connection. The startup has just pulled in $12 million to continue its pursuit of bringing AI to the edge

Since its debut it took $2.6 million in seed funding and has now filled up its A round, led by Madrona Venture Group, along with NGP Capital, Autotech Ventures and Catapult Ventures

XNOR’s technique allows things like computer vision and voice recognition to be stored and run on devices with extremely limited processing power and RAM. And we’re talking Raspberry Pi Zero here, not just like an older iPhone. If you wanted to have a camera or smart home type device in every room of your home, monitoring for voices, responding to commands, sending its video feed in to watch for unauthorized visitors or emergency situations — that constant pipe to the cloud starts getting crowded real fast. Better not to send it at all. This has the pleasant byproduct of not requiring what might be personal data to some cloud server, where you have to trust that it won’t be stored or used against your will. If the data is processed entirely on the device, it’s never shared with third parties. That’s an increasingly attractive proposition

Cheng’s mall chain, K11, and Aibee will cooperate in technologies and explore new business models to push for precise retailing, according to Aibee’s announcement on its official WeChat account. Aibee was co-founded in 2017 by Lin Yuanqing, former head of Baidu Research, and Silvio Savarese, an associate professor of computer science at Stanford University. The firm has research and development centers in Beijing and Silicon Valley

In January, Aibee raised an angel round of RMB165 million led by Kinzon Capital, and participated by Sequoia Capital China, Zhen Fund, Lenovo Capital and Incubator Group and others

Terms of the deal are not being disclosed, Bhaskar Gorti, president of Nokia Software, said in an interview. The startup had raised between $50 million and $65 million in funding (based on figures from Crunchbase and PitchBook), and PitchBook last estimated its valuation at just over $103 million in 2016. Backers of the startup included the energy giant E.ON, Novus Energy Partners, Zouk Capital and more

SpaceTime is an interesting acquisition not only because will help Nokia tap into utilising more artificial intelligence — which by many accounts has become and will be the essential cornerstone of how IT services operate — but because it’s also bringing something else to the business: customers. SpaceTime is coming to Nokia with an established set of customers, including Entergy, FedEx, NextEra Energy and Singapore Power, and Gorti said that these will continue to be customers and become an opportunity for further business

The Israel Security Authority (ISA) (Shin Bet) and venture capital fund TAU Ventures, founded by Tel Aviv University, have announced the launching of a startup accelerator in Israel. The first class will focus on early-stage entrepreneurs working in artificial intelligence (AI), primarily natural-language processing (NLP) technologies, robotics, and data science

The program, which will be called The Xcelerator, is aimed at connecting entrepreneurs who have a technological proof of concept and who are not necessarily oriented toward the homeland security industry. The first group of the program, which will begin this June, will have six startups participating and will run for four months. The participating startups will be chosen by a joint committee of professionals from the ISA and the TAU Ventures fund, and each of them will receive a $50,000 grant from the ISA, with no equity and no restrictions

The SpeechXrays consortium, which is supported by EU research and innovation investment, aims to develop and test a multi-channel biometrics solutions based on acoustic and machine vision analysis of speech, lips movement and face

With multi-million-euro funding from the European Union’s Horizon 2020 Research and Innovation Programme, Idemia leads the SpeechXrays consortium; and last week welcomed VoiceTrust, the German based Voice and Face Biometrics development company, to the consortium

A self-driving car, built by a group of University of Toronto engineering and computer science students, is “pioneering” the future for how autonomous vehicles will be designed. Their autonomous vehicle, named Zeus, won the first phase of the AutoDrive Challenge, an international driverless vehicle competition

The AutoDrive Challenge required each self-driving car to complete nine tasks, including geolocating 50 locations in the U.S., driving along a straight line, detecting and avoiding objects, and obeying road signs

The University of Toronto team plans to update the car’s software using their $30,000 prize, so it can handle more complex tasks, such as following a path between two points and bypassing moving objects. Kroeze wants Zeus to be able to handle pedestrians crossing the road by the end of the competition.

Throughout this paper, REWORK explore areas such as bias, privacy and security, moral machines and decision making as well as looking at real world examples of how AI can be used for good. Download the complimentary paper.

Insilico Medicine, a Baltimore-based next-generation artificial intelligence company specializing in the application of deep learning for target identification, drug discovery and aging research announces the publication of a new research paper in Molecular Pharmaceutics journal titled “Adversarial Threshold Neural Computer for Molecular De Novo Design”

The described Adversarial Threshold Neural Computer (ATNC) model based on the combination of Generative Adversarial Networks (GANs) with Reinforcement Learning (RL) is intended for the design

“This is a proof of concept scratching the surface of what we have in house. Stay tuned for the cool experimental validation results to be announced this Summer. I hope that part of this work integrated into our pipeline will help make the world a better and healthier place and help make perfect molecules for specific targets and multiple targets that will have a much higher chance of becoming great drugs”, said Evgeny Putin, the deep learning lead at Insilico Medicine. of novel small organic molecules with the desired set of pharmacological properties

Carnegie Mellon University today announced it will offer an undergraduate degree in artificial intelligence. The college claims the degree will be the first of its kind in the United States. The first courses for the Bachelor of Science degree will be offered this fall

A study by U.S. News and World Report released in March declared Carnegie Mellon the best computer science college in the U.S. for artificial intelligence, followed by Massachusetts Institute of Technology (MIT), Stanford University, and the University of California, Berkeley

We’re not training these students to just use tools, we’re training them to understand the science enough so that they can build the tools themselves,” Simmons told VentureBeat in a phone interview. “The main emphasis of the course is understanding how this works so that they’ll be able to go out into workforce and build the next TensorFlow, not just use it.”

AliveCor, the leader in artificial intelligence and FDA-cleared personal electrocardiogram (ECG) technology, today announced an important milestone in its work with Mayo Clinic on Long QT Syndrome (LQTS)

In an abstract published today at the Heart Rhythm Scientific Sessions conference in Boston, investigators from Mayo Clinic presented research showing that artificial intelligence (AI) using deep neural networks can successfully identify patients with congenital LQTS despite having a normal QTc on their electrocardiogram (ECG). As many as 50% of patients with genetically confirmed LQTS have a normal QT interval on the standard ECG, so identifying these patients who are at increased risk of arrhythmias and sudden cardiac death is crucial for correct diagnosis and treatment. This is especially critical when patients are exposed to medications with known QT prolonging potential

The deep neural network employed in the study generated an area under the curve of 0.83, with a specificity of 81%, sensitivity of 73%, and an overall accuracy of 79%. Importantly, the results were achieved by applying AI to data from lead I of a 12-lead ECG, which suggests that AliveCor’s KardiaMobile and KardiaBand devices may be useful in the mobile detection of patients with concealed LQTS

Linguamatics, the leading NLP-based text analytics provider for biomedical applications, today announced the launch of Linguamatics iScite, a breakthrough innovation in scientific search that puts the precision and power of Linguamatics artificial intelligence (AI) technology directly into the hands of scientists, researchers and other knowledge workers. iScite offers a modern, easy-to-use scientific search engine that provides intuitive access to AI-powered searches across key biomedical data sources and delivers insightful answers to search questions

iScite is designed as a next-generation search experience that empowers non-technical users to conduct their own NLP-based scientific searches to extract data insights. Rather than rely on time- and/or resource-crunched technical experts to create and perform searches, iScite enables users to quickly and independently find precise answers to their high-value questions

“Traditional search methods are often time-consuming, expensive and ineffective, and the results are imprecise and difficult to sift through,” said Jane Reed, head of life science strategy for Linguamatics. “With iScite, users can take advantage of the power of NLP without the traditional complexities. Our patent-pending Answer-Routing Engine interprets users’ search terms and guides them to the best possible answers to their questions. Searches are seamless across multiple content sources, and users are quickly pointed to the exact content relevant to their search without having to laboriously read through every word of the source documents.”

Researchers reported on April 23, 2018, that computers which undergo deep learning can predict the stability of planets in binary star systems more successfully than human astronomers. A study on this subject looked at what many astronomers call Tatooines, planets orbiting two stars, named for the fictional Tatooine first introduced in 1977 as Luke Skywalker’s home in the original Star Wars movie. Researchers Chris Lam and David Kipping were both, at the time, at the Cool Worlds lab at Columbia University in New York (Lam has since obtained his Ph.D. and moved on). Their study is published in the peer-reviewed journal Monthly Notices of the Royal Astronomical Societ

Also on April 23, 2018, astronomers at UC Santa Cruz reported using machine deep learning techniques to analyze images of galaxies, with the goal of understanding how galaxies form and evolve. This new study has been accepted for publication in the peer-reviewed Astrophysical Journal and is available online. In the study, researchers used computer simulations of galaxy formation to train a deep learning algorithm, which then proved surprisingly good at analyzing images of galaxies from the Hubble Space Telescope

Researchers are currently working on a new framework called Maplite which they hope will allow driverless cars to figure out roads they’ve never driven on before, without the need for 3D maps. Combining Google Maps GPS data with the car’s own LIDAR and IMU sensors, the idea is that the car can figure out the way the road is twisting and turning without needing to know exactly what lies ahead

The reason this kind of ‘map-less’ approach hasn’t really been done before is because it is generally much harder to reach the same accuracy and reliability as with detailed maps,” lead author on a related paper, Teddy Ort, told MIT News. “A system like this that can navigate just with onboard sensors shows the potential of self-driving cars being able to actually handle roads beyond the small number that tech companies have mapped.”

Ort doesn’t believe that this system will see the end of 3D-map usage, or spell a change in how self-driving cars operate more generally, chiefly because the more information autonomous vehicles have, the better. “I imagine that the self-driving cars of the future will always make some use of 3D maps in urban areas. But when called upon to take a trip off the beaten path, these vehicles will need to be as good as humans at driving on unfamiliar roads they have never seen before.”

China’s patents in the artificial intelligence (AI) industry accounted for about 22 percent of the total globally, according to an official with the Ministry of Industry and Information Technology (MIIT)

Wang Xinzhe said China had more than 2,000 artificial intelligence companies by the end of 2017. Wang made the comments at the Global AI Products Application EXPO 2018 in Suzhou city, Jiangsu Province

A bipartisan pair of senators has introduced legislation to create a national commission to guide America’s artificial intelligence investments

The language was introduced Wednesday by Sens. Joni Ernst, R-Iowa, chairman of the Senate Armed Services Committee’s Emerging Threats and Capabilities Subcommittee, and Catherine Cortez Masto, D-Nev, a member of the Committee on Commerce, Science and Transportation. The senators designed the legislation to complement language introduced in the House by Rep. Elise Stefanik, chair of the House Armed Services Committee’s Subcommittee on Emerging Threats and Capabilities

As part of that process, such a commission would complete a yearly report looking at AI through the lens of national security, economic security, public-private partnerships and investment. The commission would have 15 members appointed by Congress and executive branch leaders from the fields of defense, commerce, science and intelligence. It would also provide suggestions “maintaining a technological advantage, developments in foreign investments in AI, how to recruit leading talent in AI and STEM fields, and the risks associated with U.S., foreign countries, and non-state actors’ advances in the military employment of AI,” per an announcement

Ohio Governor John Kasich from issuing an executive order making it the latest state to allow the testing of such vehicles on its public roads. Kasich gave the go ahead for trials of autonomous vehicles on the state’s roads on Wednesday, May 9. Other states that allow self-driving cars on their streets include California, Pennsylvania, Florida, Michigan, and, as we already mentioned, Arizona

Similar to Arizona and, more recently, California, companies will have the option to put their autonomous cars on Ohio’s roads without a safety driver behind the wheel, though in this case a licensed operator will be required to monitor the car remotely and must have the means to take over if its technology malfunctions, Bloomberg reported. Waymo is already conducting tests with remote safety drivers in Arizona, and recently applied to do the same in California

Kaisch has set up a body called DriveOhio to which any accidents must be reported. DriveOhio will also work to bring public and private sectors together in a bid to advance the development and deployment of smart mobility and autonomous and connected vehicles, according to its website

Aging four-man T-59 tanks, thousands of which are being retired and scrapped after years of service, have been fitted with remote-control technology that is operated by a soldier at a nearby console equipped with a video game-style steering wheel

While China has experimented with small reconnaissance robots, drone aircraft and a driverless truck in the past, this is believed to be its first attempt to develop an unmanned tank

The People’s Liberation Army may be using the obsolete tank, the first to be domestically produced in China, for its experiments with the technology with a view to fitting more modern vehicles with it if it proves to be successful. Or they could complement newer tanks when deployed in the early stages of a battle

Now, it appears the White House itself is getting involved in bringing together key American stakeholders to discuss AI and those opportunities and challenges. According to Tony Romm and Drew Harwell of the Washington Post, the White House brought executives from major tech companies and other large corporations together this past Thursday to discuss AI and how American companies can cooperate to take advantage of new advances in these technologies

The United States has been remarkably uncoordinated when it comes to AI. While the government has released some strategic plans, it has mostly failed to follow through on coordinating more dollars towards artificial intelligence. As The New York Times noted in February, the White House has been remarkably silent on AI, despite the growing discussions around the technology

That lack of engagement from policymakers has been fine — after all, the United States is the world leader in AI research. But with other nations pouring resources and talent into the space, DC policymakers are worried that the U.S. could suddenly find itself behind the frontier of research in the space, with particular repercussions for the defense industry

According to the State Council of China, China set up a national association to promote the integration of artificial intelligence (AI) technology with medical care to improve services. At its inauguration ceremony on May 5, it was announced that the Chinese Intelligent Medicine Association will provide a platform for research, exchange and cooperation in intelligent medicine

The President of Chinese Medical Doctor Association Mr Zhang Yanling will supervise the new Chinese Intelligent Medicine Association. According to Mr Zhang, intelligent medicine will profoundly transform the medical care sector and may bring great benefits to both patients and doctors. He also added that 124 hospitals have practiced intelligent medicine in China

In China, there is an observable trend that the healthcare sector is adopting AI technologies. For instance, the ophthalmic center in Guangzhou, Guangdong province, opened the first AI clinic in China last year to diagnose cataracts with the help of an AI-assisted platform. In a clinic at the center, images of patients’ eyes are uploaded to the platform, and a diagnosis can be given within minutes. Treatment plans are also offered for doctors’ reference. The hospital claimed that the accuracy of the AI diagnoses exceeds 90%

A local government in eastern China has blamed an artificial intelligence program for insulting messages sent from its official WeChat platform to a teacher asking for help, according to a newspaper report

The woman, identified only by the nickname “Xiao Lin” submitted a complaint about unequal pay to authorities in Guichi district, Anhui province, on Wednesday, China Youth Daily reported on Monday. The replies she received read: “If you don’t speak, nobody will think you’re dumb” and “I keep hearing the sound of mosquitoes”

On Saturday evening, the Guichi government issued an apology and explanation on its official Weibo account, and said the statement had been issued not by a person but by SimSimi, an artificial intelligence conversation program. SimSimi, which learns its responses from user input, has a reputation for generating profane remarks, and has caused political scandal in the past. Last year, anti-bullying groups called for it to be banned for producing abusive content

According to The Wall Street Journal, China is close to finalizing a $47 billion investment fund that would finance semiconductor research and chip startup development. The fund, formally the China Integrated Circuit Industry Investment Fund Co., appears to be underwritten predominantly by government capital sources

Such a fund has been rumored for months, with the size of the fund ranging widely. Just two weeks ago, Reuters reported the fund would be $19 billion, while Bloomberg reported $31.5 billion two months ago. The exact number appears to be under intense negotiation among the Chinese leadership, and is also responsive to the increasingly tense trade negotiations with the United States

While China may try to play catchup in the broad category of semiconductors, it is strategically placing its money on new areas like 5G wireless and artificial intelligence-focused chips where it might become a leading provider of technology. Concerns over 5G in particular have galvanized American attention on Qualcomm and its ability to compete in what is rare virgin territory in the telecom equipment space

At Saturday’s Committee of 100 annual conference in California’s Silicon Valley, Feifei Li, chief scientist at Google Cloud AI/ML and director at the Stanford AI Lab and Vision Lab, said the administration of U.S. President Donald Trump should continue to invest in basic science, STEM (science, technology, engineering and mathematics) education, research and public universities to “invest in the future”

“If the U.S. is not willing to increase its investment in science, technology and AI, then no amount of measures against China through tariffs, through other restrictions (are) going to keep the United States’ leadership (in those fields),” former U.S. ambassador to China Gary Locke said at the C100 summit luncheon

The Trump administration has proposed cutting the federal budget, which would eliminate some research programs that affect NASA, energy research and climate and environmental science programs